1. Field of the Invention
The present invention relates to the clustering method for rosette scan images. In particular, the present invention relates to the method to array the image pixels obtained according to the rosette pattern in a two-dimensional memory, define partial clusters from the said memory with the array, and to generate clusters from the said defined partial clusters.
2. Description of the Related Art
The rosette scan image is an image formed by a single element detector""s scanning of the total field of view by the rosette pattern. The rosette scan image is frequently used by the infrared guided missile""s detector for distinguishing the real target from false targets such as flares. The rosette seeker, through the counter-rotation of the two optical elements, provides a two-dimension scan image of a target as if an infrared detector scanned the entire field of view according to the rosette pattern.
Because a rosette seeker may obtain information regarding the size or the spatial position of the target from the detected scan image, the reaction to the target, background, clutter or to flare may be differentiated. The scanning speed of the rosette pattern is higher at the center part of petals than at the outer ends of petals. Also, more scanning lines pass the center part of the pattern than the outer parts of the pattern. Due to the difference in the scanning speed and the non-linear characteristic of the rosette pattern, the detected image differs depending on the location of the subject matter within the field of view.
Furthermore, because a rosette seeker obtains the infrared image by a single element detector""s scanning, the rosette scan image has only a narrow distribution of gray scale unlike the ordinary camera image. Thus, it has been necessary to develop a signal processing method to react properly to the detected image""s changes depending on the target""s position and to correctly recognize targets such as flares.
The conventional rosette seeker has used the K-means clustering as a clustering method to differentiate images existing in the total field of view. However, the K-means clustering generates a different clustering result depending on the seed point of an initial cluster. Furthermore, the number of clusters must be determined prior to the initiation of the relevant algorithm. Thus, if a target discharges a random number of flares as countermeasures, the missile using the said method may fail to track the target. The ISODATA (Iterative Self Organizing Data Analysis Technique) method resolves such problems. The ISODATA clustering method, instead of specifying the number of clusters prior to the initiation of the algorithm process, determines the number of clusters while the algorithm is processed. Accordingly, regardless of the number of flares, all the clusters may be identified. However, as the seeker approaches the target, the number of detected clusters increases accordingly. Thus, values of the merging and splitting parameters must be modified frequently. Therefore, the ISODATA method has a drawback in that the processing time is extended as the relevant algorithm is repeated and the parameters must be modified during the tracking.
In order to resolve the above-described problems in the conventional clustering methods, the present invention intends to provide a clustering method to array image pixels, which have been obtained by a rosette pattern, in a two-dimensional memory and to cluster the image using the continuity of the data in the said memory, dispensing with the need for a seed point or the merging and splitting parameters.